scholarly journals The Interannual Variability of the Onset of the Maize Growing Season over South Africa and Zimbabwe

2005 ◽  
Vol 18 (16) ◽  
pp. 3356-3372 ◽  
Author(s):  
M. A. Tadross ◽  
B. C. Hewitson ◽  
M. T. Usman
Keyword(s):  
South Africa ◽  
Early Onset ◽  
General Circulation ◽  
Decadal Variability ◽  
Late Onset ◽  
Growing Season ◽  
General Circulation Models ◽  
Self Organizing Map ◽  
Asymmetric Component ◽  
Synoptic Conditions

Abstract Subsistence farmers within southern Africa have identified the onset of the maize growing season as an important seasonal characteristic, advance knowledge of which would aid preparations for the planting of rain-fed maize. Onset over South Africa and Zimbabwe is calculated using rainfall data from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Computing Center for Water Research (CCWR). The two datasets present similar estimates of the mean, standard deviation, and trend of onset for the common period (1979–97) over South Africa. During this period, onset has been tending to occur later in the season, in particular over the coastal regions and the Limpopo valley. However, the CCWR data (1950–97) indicate that this is part of long-term (decadal) variability. Characteristic rainfall patterns associated with late and early onset are estimated using a self-organizing map (SOM). Late onset is associated with heavier rainfall over the subcontinent. When onset is early over Zimbabwe, there is an increased frequency of more intense rainfall over northeast Madagascar during the preceding August. Accompanying these intense events is an increased frequency of positive 500-hPa geopotential height anomalies to the southeast of the continent. Similar positive height anomalies are also frequently present during early onset. The study indicates that onset variability is partly forced by synoptic conditions, and the successful use of general circulation models to estimate onset will depend on their simulation of the zonally asymmetric component of the westerly circulation.

scholarly journals An assessment of the skill of downscaled GCM outputs in simulating historical patterns of rainfall variability in South Africa

2013 ◽  
Vol 45 (1) ◽  
pp. 134-147 ◽  
Author(s):  
D. A. Hughes ◽  
S. Mantel ◽  
T. Mohobane
Keyword(s):  
South Africa ◽  
Water Resources ◽  
General Circulation ◽  
Hydrological Model ◽  
Rainfall Variability ◽  
General Circulation Models ◽  
Local Scale ◽  
Coastal Areas ◽  
General Applicability ◽  
Modelling Studies

Uncertainties associated with General Circulation Models (GCMs) and the downscaling methods used for regional or local scale hydrological modelling can result in substantial differences in estimates of future water resources availability. This paper assesses the skill of nine statistically downscaled GCMs in reproducing historical climate for 15 catchments in five regions of South Africa. The identification of skilled GCMs may reduce the uncertainty in future predictions and the focus is on rainfall skill as the GCMs show very similar patterns of change in temperature. The skill tests were designed to assess whether the GCMs are able to realistically reproduce precipitation distribution statistics and patterns of seasonality, persistence and extremes. Some models are consistently less skilful for the regions assessed, while some are generally more skilful with some regionally specific exceptions. There are differences in the GCMs skill across the different regions and in the skill ranking between coastal areas and inland regions. However, only a limited reduction in uncertainty is achieved when using only the downscaled GCM outputs identified as being skilled in a hydrological model for one of the regions. Further modelling studies are required to determine the general applicability of this observation.

scholarly journals Conjunction of wavelet-entropy and SOM clustering for multi-GCM statistical downscaling

2018 ◽  
Vol 50 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Aida Hosseini Baghanam ◽  
Vahid Nourani ◽  
Mohammad-Ali Keynejad ◽  
Hassan Taghipour ◽  
Mohammad-Taghi Alami
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Self Organizing Map ◽  
Climate Data ◽  
Wavelet Entropy ◽  
Som Clustering ◽  
Artificial Neural Network Ann

Abstract Important issues in statistical downscaling of general circulation models (GCMs) is to select dominant large-scale climate data (predictors). This study developed a predictor screening framework, which integrates wavelet-entropy (WE) and self-organizing map (SOM) to downscale station rainfall. WEs were computed as the representatives of predictors and fed into the SOM to cluster the predictors. SOM-based clustering of predictors according to WEs could lead to physically meaningful selection of the dominant predictors. Then, artificial neural network (ANN) as the statistical downscaling method was developed. To assess the advantages of different GCMs, multi-GCM ensemble approach was used by Can-ESM2, BNU-ESM, and INM-CM4 GCMs. Moreover, NCEP reanalysis data were used to calibrate downscaling model as well for comparison purposes. The calibration, validation, and projection of the proposed model were performed during January 1951 to December 1991, January 1992 to December 2005 and January 2017 to December 2100, respectively. The proposed data screening model could reduce the dimensionality of data and select appropriate predictors for generalizing future rainfall. Results showed better performance of ANN than multiple linear regression (MLR) model. The projection results yielded 29% and 21% decrease of rainfall at the study area for 2017–2050 under RCPs 4.5 and 8.5, respectively.

Climate Change and Crop Production in Africa

2021 ◽  
pp. 204-212
Author(s):  
Zerihun Yohannes Amare
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Crop Production ◽  
Agricultural Sector ◽  
Human Life ◽  
Primary Source ◽  
Growing Season ◽  
General Circulation Models ◽  
High Heat ◽  
Sub Saharan

Agriculture, particularly crop production, is an economic activity that is highly dependent upon weather and climate in order to produce the food and fiber necessary to sustain human life. The vulnerability of agriculture to climate change and variability is an issue of major importance to the international scientific community. Greenhouse gas (GHG)-induced climate change would very likely result in significant damage in the agricultural sector in sub-Saharan Africa because the region already endures high heat and low precipitation. General circulation models (GCMs) are the primary source of climate change scenarios which make projections about the degree and timing of climate change. Agriculture has always been dependent on the variability of the climate for the growing season and the state of the land at the start of the growing season. The key for adaptation for crop production to climate change is the predictability of the conditions. What is required is an understanding of the effect on the changing climate on land, water, and temperature.

scholarly journals The Predictability of Tropical Pacific Decadal Variability: Insights from Attractor Reconstruction

2019 ◽  
Vol 76 (3) ◽  
pp. 801-819 ◽  
Author(s):  
Nandini Ramesh ◽  
Mark A. Cane
Keyword(s):  
General Circulation ◽  
Decadal Variability ◽  
General Circulation Models ◽  
Tropical Pacific ◽  
The Other ◽  
Intermediate Complexity ◽  
Pacific Decadal Variability ◽  
Attractor Reconstruction ◽  
Climatic Impacts ◽  
The Tropical Pacific

Abstract Tropical Pacific decadal variability (TPDV), though not the totality of Pacific decadal variability, has wide-ranging climatic impacts. It is currently unclear whether this phenomenon is predictable. In this study, we reconstruct the attractor of the tropical Pacific system in long, unforced simulations from an intermediate-complexity model, two general circulation models (GCMs), and the observations with the aim of assessing the predictability of TPDV in these systems. We find that in the intermediate-complexity model, positive (high variance, El Niño–like) and negative (low variance, La Niña–like) phases of TPDV emerge as a pair of regime-like states. The observed system bears resemblance to this behavior, as does one GCM, while the other GCM does not display this structure. However, these last three time series are too short to confidently characterize the full distribution of interdecadal variability. The intermediate-complexity model is shown to lie in highly predictable parts of its attractor 37% of the time, during which most transitions between TPDV regimes occur. The similarities between the observations and this system suggest that the tropical Pacific may be somewhat predictable on interdecadal time scales.

Multi-decadal climate variability, New South Wales, Australia

2004 ◽  
Vol 49 (7) ◽  
pp. 133-140 ◽  
Author(s):  
S.W. Franks
Keyword(s):  
Climate Variability ◽  
General Circulation ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
New South ◽  
New South Wales ◽  
General Circulation Models ◽  
Drought Risk ◽  
Decadal Climate Variability ◽  
South Wales

Traditional hydrological risk estimation has treated the observations of hydro-climatological extremes as being independent and identically distributed, implying a static climate risk. However, recent research has highlighted the persistence of multi-decadal epochs of distinct climate states across New South Wales (NSW), Australia. Climatological studies have also revealed multi-decadal variability in the magnitude and frequency of El Niño/Southern Oscillation (ENSO) impacts. In this paper, examples of multi-decadal variability are presented with regard to flood and drought risk. The causal mechanisms for the observed variability are then explored. Finally, it is argued that the insights into climate variability provide (a) useful lead time for forecasting seasonal hydrological risk, (b) a strong rationale for a new framework for hydrological design and (c) a strong example of natural climate variability for use in the testing of General Circulation Models of climate change.

Climate Change and Crop Production in Africa

2022 ◽  
pp. 1293-1302
Author(s):  
Zerihun Yohannes Amare
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Crop Production ◽  
Agricultural Sector ◽  
Human Life ◽  
Primary Source ◽  
Growing Season ◽  
General Circulation Models ◽  
High Heat ◽  
Sub Saharan

Agriculture, particularly crop production, is an economic activity that is highly dependent upon weather and climate in order to produce the food and fiber necessary to sustain human life. The vulnerability of agriculture to climate change and variability is an issue of major importance to the international scientific community. Greenhouse gas (GHG)-induced climate change would very likely result in significant damage in the agricultural sector in sub-Saharan Africa because the region already endures high heat and low precipitation. General circulation models (GCMs) are the primary source of climate change scenarios which make projections about the degree and timing of climate change. Agriculture has always been dependent on the variability of the climate for the growing season and the state of the land at the start of the growing season. The key for adaptation for crop production to climate change is the predictability of the conditions. What is required is an understanding of the effect on the changing climate on land, water, and temperature.

scholarly journals The Study of Frost Occurrence in Free State Province of South Africa

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Mokhele Edmond Moeletsi ◽  
Mphethe Tongwane ◽  
Mitsuru Tsubo
Keyword(s):  
South Africa ◽  
Early Onset ◽  
Late Onset ◽  
Kendall Test ◽  
Free State ◽  
Free State Province ◽  
Growing Period ◽  
Frost Free Period ◽  
Light Medium

The study investigated the cessation, onset, and duration of light, medium, and heavy frost in Free State province of South Africa using minimum temperatures from 1960 to 2015. Trends in the frost indices were assessed using the Man-Kendall test. Onset of frost varied spatially with earlier onset over the northern, eastern, and southeastern parts. Areas of early onset also experience late cessation of frost resulting in shorter growing period of less than 240 days. The western parts have longer growing period exceeding 240 days due to earlier cessation of frost and relatively late onset of frost. Trends for the frost-free period (growing period) show contrasting negative and positive trends with isolated significant trends.

scholarly journals Climate Change Dynamics and Imperatives for Food Security in Nigeria

2016 ◽  
Vol 47 (2) ◽  
pp. 151
Author(s):  
Olumide D. Onafeso ◽  
Cornelius O. Akanni ◽  
Bamidele A. Badejo
Keyword(s):  
Food Security ◽  
Crop Yield ◽  
General Circulation ◽  
Decadal Variability ◽  
General Circulation Models ◽  
Northern Region ◽  
Livestock Farming ◽  
Growing Seasons ◽  
Bivariate Correlation ◽  
Spatio Temporal

Decadal variability in African rainfall is projected from General Circulation Models (GCMs) to continue under elevated greenhouse gas scenarios. Effects on rain intensity, spatio-temporal variability of growing seasons, flooding, drought, and land-use change impose feedbacks at regional-local scales. Yet, empirical knowledge of associated impacts on crop yield is limited; thus, we examined the imperatives for food security in Nigeria. Bivariate correlation and multiple regression suggests impending drought in the northern region where livestock farming is predominant. Relative contributions of climate independent variables in determining crop yield by backward selection procedures with stepwise approach indexed the impacts of annual climate variability by a parameter computed as annual yield minus mean annual yield divided by the standard deviation. Results show Z-distribution approximately 5 to + 5, when < 3 or > 3 indicate impacts significant at 95% confidence levels. In conclusion, we established the interwoven relationship between climatic change and food security.

NEONATAL SEPSIS AND IDENTIFICATION OF RISK FACTORS: STUDY IN AVBRH HOSPITAL SAWANGI

2019 ◽  
Vol 3 (6) ◽  
Author(s):  
Pramod P. Singhavi
Keyword(s):  
Risk Factors ◽  
Neonatal Sepsis ◽  
Early Onset ◽  
Late Onset ◽  
Signs And Symptoms ◽  
Premature Rupture ◽  
Maternal Risk ◽  
Late Onset Sepsis ◽  
Early Onset Sepsis ◽  
Meconium Stained Amniotic Fluid

Introduction: India has the highest incidence of clinical sepsis i.e.17,000/ 1,00,000 live births. In Neonatal sepsis septicaemia, pneumonia, meningitis, osteomyelitis, arthritis and urinary tract infections can be included. Mortality in the neonatal period each year account for 41% (3.6 million) of all deaths in children under 5 years and most of these deaths occur in low income countries and about one million of these deaths are due to infectious causes including neonatal sepsis, meningitis, and pneumonia. In early onset neonatal sepsis (EOS) Clinical features are non-specific and are inefficient for identifying neonates with early-onset sepsis. Culture results take up to 48 hours and may give false-positive or low-yield results because of the antenatal antibiotic exposure. Reviews of risk factors has been used globally to guide the development of management guidelines for neonatal sepsis, and it is similarly recommended that such evidence be used to inform guideline development for management of neonatal sepsis. Material and Methods: This study was carried out using institution based cross section study . The total number neonates admitted in the hospital in given study period was 644, of which 234 were diagnosed for neonatal sepsis by the treating pediatrician based on the signs and symptoms during admission. The data was collected: Sociodemographic characteristics; maternal information; and neonatal information for neonatal sepsis like neonatal age on admission, sex, gestational age, birth weight, crying immediately at birth, and resuscitation at birth. Results: Out of 644 neonates admitted 234 (36.34%) were diagnosed for neonatal sepsis by the paediatrician based on the signs and symptoms during admission. Of the 234 neonates, 189 (80.77%) infants were in the age range of 0 to 7 days (Early onset sepsis) while 45 (19.23%) were aged between 8 and 28 days (Late onset sepsis). Male to female ratio in our study was 53.8% and 46% respectively. Out of total 126 male neonates 91(72.2%) were having early onset sepsis while 35 (27.8%) were late onset type. Out of total 108 female neonates 89(82.4%) were having early onset sepsis while 19 (17.6%) were late onset type. Maternal risk factors were identified in 103(57.2%) of early onset sepsis cases while in late onset sepsis cases were 11(20.4%). Foul smelling liquor in early onset sepsis and in late onset sepsis was 10(5.56%) and 2 (3.70%) respectively. In early onset sepsis cases maternal UTI, Meconium stained amniotic fluid, Multipara and Premature rupture of membrane was seen in 21(11.67%), 19 (10.56%), 20(11.11%) and 33 (18.33%) cases respectively. In late onset sepsis cases maternal UTI, Meconium stained amniotic fluid, Multipara and Premature rupture of membrane was seen in 2 (3.70%), 1(1.85%), 3 (5.56%) and 3 (5.56%) cases respectively. Conclusion: Maternal risk identification may help in the early identification and empirical antibiotic treatment in neonatal sepsis and thus mortality and morbidity can be reduced.

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